Diverticular disease is one of the most prevalent disorders in western societies, and complications of diverticulosis are frequent, costly and often recurrent. Identification of individuals at high risk for these complications is of great clinical importance. However, few risk factors have been identified, and no preventative strategies exist short of segmental colectomy. The role of human intestinal microbiota in disease is increasingly being recognized. Recent advances in DNA sequencing technology now enable cost-effective, large-scale profiling of the intestinal microbiota, and provide a new quantitative tool for the study of gastrointestinal disorders. The intestinal microbiota represent an attractive target for study in diverticular disease since they can be sampled, providing the basis for a potential biomarkers and preventative interventions. The overall goal of this proposal is to profile the intestinal microbiota in both patients with asymptomatic diverticulosis and those with diverticulosis complicated by acute diverticulitis. We plan to use a combination of state-of-the-art molecular and novel metagenomic approaches, and to determine whether quantitative analysis of the intestinal microbiome can be used to differentiate diverticular disease phenotypes. Uncovering such differences would be of great potential clinical significance, since they could be modeled to (i) enable outcome prediction and risk stratification; (ii) provide avenues for treatment and prevention, and (iii) reveal insight into pathogenesis. In pursuit of this goal, we plan to profile the intestinal microbiome in diverticular disease using two parallel study cohorts: (i) 100 patients with asymptomatic diverticulosis recruited prospectively from the outpatient endoscopy units of two large teaching hospitals; and (ii) 100 prospectively identified patients with diverticulosis complicated by acute diverticulitis. Replicate fecal DNA samples will be collected longitudinally from each study individual using well-tested methods. We will then perform intestinal microbiome profiling using a combination of metagenomic Terminal Restriction Fragment Polymorphism (tRFLP) analysis and a novel digital 16S fingerprinting approach utilizing next-generation sequencing. These data will yield deep, high-resolution fingerprints of the intestinal microbial metagenome in each disease population, which can then be compared to identify composite biomarkers that predict disease complications.